George Abdelmalek MD , Harjot Uppal MBA , Daniel Garcia BS , Joseph Farshchian MD , Arash Emami MD , Andrew McGinniss MD
{"title":"利用ChatGPT制作常见手部疾病的患者教育材料","authors":"George Abdelmalek MD , Harjot Uppal MBA , Daniel Garcia BS , Joseph Farshchian MD , Arash Emami MD , Andrew McGinniss MD","doi":"10.1016/j.jhsg.2024.10.002","DOIUrl":null,"url":null,"abstract":"<div><h3>Purpose</h3><div>Many adults in the United States possess basic or below basic health literacy skills, making it essential for patient education materials (PEMs) to be presented at or below a sixth-grade reading level. We evaluate the readability of PEMs generated by ChatGPT 3.5 and 4.0 for common hand conditions.</div></div><div><h3>Methods</h3><div>We used Chat Generative Pre-Trained Transformer (ChatGPT) 3.5 and 4.0 to generate PEMs for 50 common hand pathologies. Two consistent questions were asked to minimize variability: 1. “Please explain [Condition] to a patient at a sixth-grade reading level, including details on anatomy, symptoms, doctors' examination, and treatment (both surgical and nonsurgical).” 2. “Create a detailed patient information sheet for the general patient population at a sixth-grade reading level explaining [Condition], including points such as anatomy, symptoms, physical examination, and treatment (both surgical and nonsurgical).” Before asking the second question, a priming phase was conducted where ChatGPT 3.5 and 4.0 were presented with a text sample written at a sixth-grade reading level and informed that this was the desired output level. Multiple readability tests were used to evaluate the output, with a consensus reading level created from the results of all eight readability scores. Statistical analyses were performed using SAS 9.4.</div></div><div><h3>Results</h3><div>ChatGPT 4.0 successfully produced 28% of its responses at the appropriate reading level following the priming phase, compared to none by ChatGPT 3.5. ChatGPT 4.0 showed superior performance across all readability metrics.</div></div><div><h3>Conclusions</h3><div>ChatGPT 4.0 is a more effective tool than ChatGPT 3.5 for generating PEMs at a sixth-grade reading level for common hand conditions.</div></div><div><h3>Clinical relevance</h3><div>The results suggest that Artificial Intelligence could significantly enhance patient education and health literacy with further refinement.</div></div>","PeriodicalId":36920,"journal":{"name":"Journal of Hand Surgery Global Online","volume":"7 1","pages":"Pages 37-40"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Leveraging ChatGPT to Produce Patient Education Materials for Common Hand Conditions\",\"authors\":\"George Abdelmalek MD , Harjot Uppal MBA , Daniel Garcia BS , Joseph Farshchian MD , Arash Emami MD , Andrew McGinniss MD\",\"doi\":\"10.1016/j.jhsg.2024.10.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Purpose</h3><div>Many adults in the United States possess basic or below basic health literacy skills, making it essential for patient education materials (PEMs) to be presented at or below a sixth-grade reading level. We evaluate the readability of PEMs generated by ChatGPT 3.5 and 4.0 for common hand conditions.</div></div><div><h3>Methods</h3><div>We used Chat Generative Pre-Trained Transformer (ChatGPT) 3.5 and 4.0 to generate PEMs for 50 common hand pathologies. Two consistent questions were asked to minimize variability: 1. “Please explain [Condition] to a patient at a sixth-grade reading level, including details on anatomy, symptoms, doctors' examination, and treatment (both surgical and nonsurgical).” 2. “Create a detailed patient information sheet for the general patient population at a sixth-grade reading level explaining [Condition], including points such as anatomy, symptoms, physical examination, and treatment (both surgical and nonsurgical).” Before asking the second question, a priming phase was conducted where ChatGPT 3.5 and 4.0 were presented with a text sample written at a sixth-grade reading level and informed that this was the desired output level. Multiple readability tests were used to evaluate the output, with a consensus reading level created from the results of all eight readability scores. Statistical analyses were performed using SAS 9.4.</div></div><div><h3>Results</h3><div>ChatGPT 4.0 successfully produced 28% of its responses at the appropriate reading level following the priming phase, compared to none by ChatGPT 3.5. ChatGPT 4.0 showed superior performance across all readability metrics.</div></div><div><h3>Conclusions</h3><div>ChatGPT 4.0 is a more effective tool than ChatGPT 3.5 for generating PEMs at a sixth-grade reading level for common hand conditions.</div></div><div><h3>Clinical relevance</h3><div>The results suggest that Artificial Intelligence could significantly enhance patient education and health literacy with further refinement.</div></div>\",\"PeriodicalId\":36920,\"journal\":{\"name\":\"Journal of Hand Surgery Global Online\",\"volume\":\"7 1\",\"pages\":\"Pages 37-40\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Hand Surgery Global Online\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2589514124001956\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Hand Surgery Global Online","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2589514124001956","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
Leveraging ChatGPT to Produce Patient Education Materials for Common Hand Conditions
Purpose
Many adults in the United States possess basic or below basic health literacy skills, making it essential for patient education materials (PEMs) to be presented at or below a sixth-grade reading level. We evaluate the readability of PEMs generated by ChatGPT 3.5 and 4.0 for common hand conditions.
Methods
We used Chat Generative Pre-Trained Transformer (ChatGPT) 3.5 and 4.0 to generate PEMs for 50 common hand pathologies. Two consistent questions were asked to minimize variability: 1. “Please explain [Condition] to a patient at a sixth-grade reading level, including details on anatomy, symptoms, doctors' examination, and treatment (both surgical and nonsurgical).” 2. “Create a detailed patient information sheet for the general patient population at a sixth-grade reading level explaining [Condition], including points such as anatomy, symptoms, physical examination, and treatment (both surgical and nonsurgical).” Before asking the second question, a priming phase was conducted where ChatGPT 3.5 and 4.0 were presented with a text sample written at a sixth-grade reading level and informed that this was the desired output level. Multiple readability tests were used to evaluate the output, with a consensus reading level created from the results of all eight readability scores. Statistical analyses were performed using SAS 9.4.
Results
ChatGPT 4.0 successfully produced 28% of its responses at the appropriate reading level following the priming phase, compared to none by ChatGPT 3.5. ChatGPT 4.0 showed superior performance across all readability metrics.
Conclusions
ChatGPT 4.0 is a more effective tool than ChatGPT 3.5 for generating PEMs at a sixth-grade reading level for common hand conditions.
Clinical relevance
The results suggest that Artificial Intelligence could significantly enhance patient education and health literacy with further refinement.